Papers, presentations, reports and more, written in LaTeX and published by our community. Search or browse below.
Design of a Noninvasive Pulse Rate Meter
The purpose of this project was to design a noninvasive pulse rate meter. The design team decided to create a four-stage system for identifying the pulse using optical sensors. The first stage is the input, where an infrared LED shines light at a patient's finger while a photodiode receives light on the other end. The change in blood volume in the patient's finger changes the light in the patient's finger, which creates a current across the photodiode. The second stage is the current-to-voltage converter, whereby the current created by the change in light levels effects a change in voltage. This voltage is passed to the third stage, which is filtering, which attenuates the low-frequency DC offset as well as the high-frequency noise. The final stage is amplification, whereby the filtered signal is amplified so that it may be read by other means, such as a microcontroller.
Cobi Finkelstein and Erin LaBounty
Newton's Method Cycles
Based on the paper Sometimes Newton's Method Cycles, we first asked ourselves if there were any Newtonian Method Cycle functions which have non-trivial guesses. We encountered a way to create functions that cycle between a set number of points with any initial, non-trivial guesses when Newton's Method is applied. We exercised these possibilities through the methods of 2-cycles, 3-cycles and 4-cycles. We then generalized these cycles into k-cycles. After generalizing Newton's Method, we found the conditions that skew the cycles into a spiral pattern which will either converge, diverge or become a near-cycle. Once we obtained all this information, we explored additional questions that rose up from our initial exploration of Newton's Method.
Edgara Vanoye & MacKay Martin
V-Formation as Optimal Control
We present a new formulation of the V-formation problem for migrating birds in terms of model predictive control (MPC).
Air quality predictor
Machine learning project report. The project aimed at predicting air quality based on weather and its code is available at https://github.com/annisall/mlproject.